Students have engineering on the brain

With the recent launch of MIT’s Institute for Medical Engineering and Science, MIT News examines research with the potential to reshape medicine and health care through new scientific knowledge, novel treatments and products, better management of medical data, and improvements in health-care delivery.

Neurotechnology may sound dauntingly complex, but in practice it can include ideas as straightforward as recognizing computer users by the exact way they press buttons.

One such prototype, developed at MIT, works by sensing subtle differences in the timing and pressure applied by a user in pressing a particular sequence on a touchscreen divided into four colored squares. In a recent demonstration of the system, graduate student Ralph Rodriguez activated a tablet device by tapping the colored squares in the right sequence. He then relocked the device, revealed the correct color sequence, and passed it around the room. Even knowing the right code, none of the 20 people could get the device to unlock.

The idea behind the system is to protect sensitive user data, such as passwords and financial information stored on a mobile device, in case the device is stolen. Rodriguez already has three patents pending on the system, and has started a company to develop it.

This new approach to user authentication was just one of several concepts for neurotech-based businesses that emerged from the latest version of an MIT course called “Neurotechnology Ventures,” which has been taught every year since 2007. The class, co-taught by MIT Media Lab associate professor Ed Boyden and lecturer Joost Bonsen, encourages students to develop businesses based on concepts derived from the study of the brain, psychology, artificial intelligence, neurobiology or related fields.

Many of the ventures exist at the cutting edge of neuroscience research. For inspiration, Boyden described a project in which robots were developed for mapping neural activity in the brain, using an automated system of probes inserted into brain tissue. When the student who developed it, a visiting PhD student from Georgia Tech, presented the invention at a conference, “people immediately started asking for one,” Boyden says.

A wide variety of business concepts emerge from the class. Recent examples include a system for measuring the emotional state of visitors to a website; an automated system for recording the precise location of a probe’s insertion into the brain, so as to map that spot for follow-up treatment or evaluation; and a simple, eyeglasses-mounted diagnostic device that can characterize vestibular disorders, epilepsy and concussions.

One recent class project has now become a startup called Daily Feats, which produces an app to help people set incremental goals for everything from losing weight to being better parents. Users receive reminders on their cellphones to help them meet those goals.

The roots of this course are in discussions Boyden and Bonsen had 15 years ago as MIT students, along with Rutledge Ellis-Behnke, now a research affiliate in the Department of Brain and Cognitive Sciences. “We were thinking how technology was going to have a lot of impact, and could play an eventual role in helping treat these brain disorders,” Boyden says. Broadly defined, brain-related disorders — everything from sleep disorders to depression to addiction — affect at least a billion people worldwide, he says.

Yet, Boyden says, most treatments for such disorders “have been found by serendipity,” and in the late 1990s there was little systematic research aimed at finding solutions to these problems. While almost every field of science has an associated field of engineering research, Bonsen says, this was not true of brain and cognitive science in its infancy. MIT was a pioneer in neurotechnology, establishing the McGovern Institute Neurotechnology (MINT) program in 2006.

“Neurotechnology Ventures” was first offered in the spring of 2007; Boyden, Bonsen and Ellis-Behnke initially co-taught the class. Then as now, speakers came to discuss their own efforts — in neurodiagnostics, neurotherapeutics, and analytical and research-based concepts — to develop new technologies and bring them to market. “It’s really a broad swath of technology,” Bonsen says.

Already, some of the projects spawned in the class have gone on to win prizes in contests such as MIT’s 100K Entrepreneurship Competition; several are now in the process of commercialization.

“There’s not a lot of precedent for neurotechnology entrepreneurship,” Boyden says. “That’s part of the fun, because there isn’t a cookbook to follow. The students have to experience the joys and perils of being pioneers. I learn a lot by helping students struggle with truly difficult problems.”

Boyden and Bonsen say they believe that neurotechnology is poised to take off, much as biotechnology was two decades ago. “We haven’t yet seen the founding of the Biogen or Genzyme of the neurotech field,” Bonsen says. “But I fully suspect that analogs to those companies are being born or blossoming now.”

And to help bring that about, Boyden adds, “If our class can help get a few neurotechnology companies going that seed the Silicon Valley of neurotech, that would be very exciting.”

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Complex brain function depends on flexibility

Over the past few decades, neuroscientists have made much progress in mapping the brain by deciphering the functions of individual neurons that perform very specific tasks, such as recognizing the location or color of an object.

However, there are many neurons, especially in brain regions that perform sophisticated functions such as thinking and planning, that don’t fit into this pattern. Instead of responding exclusively to one stimulus or task, these neurons react in different ways to a wide variety of things. MIT neuroscientist Earl Miller first noticed these unusual activity patterns about 20 years ago, while recording the electrical activity of neurons in animals that were trained to perform complex tasks.

“We started noticing early on that there are a whole bunch of neurons in the prefrontal cortex that can’t be classified in the traditional way of one message per neuron,” recalls Miller, the Picower Professor of Neuroscience at MIT and a member of MIT’s Picower Institute for Learning and Memory.

In a paper appearing in Nature on May 19, Miller and colleagues at Columbia University report that these neurons are essential for complex cognitive tasks, such as learning new behavior. The Columbia team, led by the study’s senior author, Stefano Fusi, developed a computer model showing that without these neurons, the brain can learn only a handful of behavioral tasks.

“You need a significant proportion of these neurons,” says Fusi, an associate professor of neuroscience at Columbia. “That gives the brain a huge computational advantage.”

Lead author of the paper is Mattia Rigotti, a former grad student in Fusi’s lab.

Multitasking neurons

Miller and other neuroscientists who first identified this neuronal activity observed that while the patterns were difficult to predict, they were not random. “In the same context, the neurons always behave the same way. It’s just that they may convey one message in one task, and a totally different message in another task,” Miller says.

For example, a neuron might distinguish between colors during one task, but issue a motor command under different conditions.

Miller and colleagues proposed that this type of neuronal flexibility is key to cognitive flexibility, including the brain’s ability to learn so many new things on the fly. “You have a bunch of neurons that can be recruited for a whole bunch of different things, and what they do just changes depending on the task demands,” he says.

At first, that theory encountered resistance “because it runs against the traditional idea that you can figure out the clockwork of the brain by figuring out the one thing each neuron does,” Miller says.

For the new Nature study, Fusi and colleagues at Columbia created a computer model to determine more precisely what role these flexible neurons play in cognition, using experimental data gathered by Miller and his former grad student, Melissa Warden. That data came from one of the most complex tasks that Miller has ever trained a monkey to perform: The animals looked at a sequence of two pictures and had to remember the pictures and the order in which they appeared.

During this task, the flexible neurons, known as “mixed selectivity neurons,” exhibited a great deal of nonlinear activity — meaning that their responses to a combination of factors cannot be predicted based on their response to each individual factor (such as one image).

Expanding capacity

Fusi’s computer model revealed that these mixed selectivity neurons are critical to building a brain that can perform many complex tasks. When the computer model includes only neurons that perform one function, the brain can only learn very simple tasks. However, when the flexible neurons are added to the model, “everything becomes so much easier and you can create a neural system that can perform very complex tasks,” Fusi says.

The flexible neurons also greatly expand the brain’s capacity to perform tasks. In the computer model, neural networks without mixed selectivity neurons could learn about 100 tasks before running out of capacity. That capacity greatly expanded to tens of millions of tasks as mixed selectivity neurons were added to the model. When mixed selectivity neurons reached about 30 percent of the total, the network’s capacity became “virtually unlimited,” Miller says — just like a human brain.

Mixed selectivity neurons are especially dominant in the prefrontal cortex, where most thought, learning and planning takes place. This study demonstrates how these mixed selectivity neurons greatly increase the number of tasks that this kind of neural network can perform, says John Duncan, a professor of neuroscience at Cambridge University.

“Especially for higher-order regions, the data that have often been taken as a complicating nuisance may be critical in allowing the system actually to work,” says Duncan, who was not part of the research team.

Miller is now trying to figure out how the brain sorts through all of this activity to create coherent messages. There is some evidence suggesting that these neurons communicate with the correct targets by synchronizing their activity with oscillations of a particular brainwave frequency.

“The idea is that neurons can send different messages to different targets by virtue of which other neurons they are synchronized with,” Miller says. “It provides a way of essentially opening up these special channels of communications so the preferred message gets to the preferred neurons and doesn’t go to neurons that don’t need to hear it.”

The research was funded by the Gatsby Foundation, the Swartz Foundation and the Kavli Foundation.

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Scientists image brain structures that deteriorate in Parkinson’s

A new imaging technique developed at MIT offers the first glimpse of the degeneration of two brain structures affected by Parkinson’s disease.

The technique, which combines several types of magnetic resonance imaging (MRI), could allow doctors to better monitor patients’ progression and track the effectiveness of potential new treatments, says Suzanne Corkin, MIT professor emerita of neuroscience and leader of the research team. The first author of the paper is David Ziegler, who received his PhD in brain and cognitive sciences from MIT in 2011. 

The study, appearing in the Nov. 26 online edition of the Archives of Neurology, is also the first to provide clinical evidence for the theory that Parkinson’s neurodegeneration begins deep in the brain and advances upward.

“This progression has never been shown in living people, and that’s what was special about this study. With our new imaging methods, we can see these structures more clearly than anyone had seen them before,” Corkin says.

Parkinson’s disease currently affects 1 to 2 percent of people over 65, totaling five million people worldwide. The disease gradually destroys the brain cells that control movement, leaving most patients wheelchair-bound and completely dependent on caregivers. “A major obstacle to research on the causes and progression of this disease has been a lack of effective brain imaging methods for the areas affected by the disease,” Ziegler says.  

In 2004, Heiko Braak, an anatomist at Johann Wolfgang Goethe University in Frankfurt, Germany, classified Parkinson’s disease into six stages, based on the appearances of the affected brain structures. He proposed that during the earliest stages, a structure deep inside the brain, known as the substantia nigra, begins to degenerate. This structure is critical for movement and also plays important roles in reward and addiction.

Later, Braak proposed, degeneration spreads outward to a brain region known as the basal forebrain. This area, located behind the eyes, includes several structures that produce acetylcholine, a neurotransmitter important for learning and memory.

Neuropathologists (scientists who study the brains of deceased patients) had found evidence for this sequence of events, but it had never been observed in living patients because the substantia nigra, deep within the brain, is so difficult to image with conventional MRI.

To overcome that, the MIT team used four types of MRI scans, each of which uses slightly different magnetic fields, generating different images. By combining these scans, the researchers created composite images of each patient’s brain that clearly show the substantia nigra and basal forebrain. “Our new MRI methods provide an unparalleled view of these two structures, allowing us to calculate the precise volumes of each structure,” Ziegler says.

After scanning normal brains, the researchers studied 29 early-stage Parkinson’s patients. They found significant loss of volume in the substantia nigra early on, followed by loss of basal forebrain volume later in the disease, as predicted by Braak.

The findings appear to correlate with the appearance of symptoms in Parkinson’s patients, says Joel Perlmutter, a professor of neurology at the Washington University School of Medicine. “This suggests that two different systems of the brain — one dopaminergic and associated with motor control, and one cholinergic and associated with cognitive function — have different timing,” Perlmutter says.

In future studies, this MRI technique could be used to follow patients over time and measure whether degeneration of the two areas is correlated or if they deteriorate independently of one another, Corkin says.

This approach could also give doctors a new way to monitor how their patients are responding to treatment, she says. (Most patients are treated with dopamine, which helps to overcome the loss of dopamine-producing neurons in the substantia nigra.) Researchers could also use the new imaging tools to determine the effects of potential new treatments.

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New insights into how brain synapses transmit information

Throughout the animal kingdom, cells encapsulate molecules and proteins — that they move within or between — in tiny vesicles, which release their contents when they fuse with another membrane. Vesicles also package the chemical signals, or neurotransmitters, that leap from neuron to neuron in the brain’s communication network, but neurons more tightly control the release of these signals. In schizophrenia, Parkinson’s disease and other neurological disorders, however, this control breaks down, which may contribute to deficits in information processing. And researchers are seeking an explanation for the loss of the normal control mechanism.

Two new MIT studies now demonstrate how neurons have adapted the cell’s standard fusion machinery to regulate the release of neurotransmitters at the neuron’s chemical junctions called synapses.

“We show that an interplay between two proteins, complexin and synaptotagmin, controls the vesicle fusion machinery in neurons, and that both proteins are necessary to trigger normal information flow and prevent uncontrolled spontaneous release,” says J. Troy Littleton, who led both studies and is an investigator in the Picower Institute for Learning and Memory and the Department of Biology and Department of Brain and Cognitive Sciences (BCS). The papers appear in the Dec. 2, 2012, and Jan. 2, 2013, issues of the Journal of Neuroscience.

Neurons have specialized needs, and one is to release neurotransmitters when the cell receives an electrical impulse that shoots down the axon to the synapses — typically in response to some stimulation. This impulse causes calcium to rush into the cell, which triggers the release of neurotransmitters across the synaptic gap to communicate with the next neuron. This neurotransmitter release is called an evoked response, as opposed to a spontaneous release (or “mini”), in which a small number of vesicles occasionally fuse without stimulation.

“So the first modification a neuron must make to the fusion machinery is to sense calcium,” says Jihye Lee, a postdoctoral associate in the Littleton lab and first author of the Jan. 2 paper that examines the role synaptotagmin plays in calcium sensing.

Synaptotagmin is a protein localized to the neuronal vesicles, with two calcium-binding domains, C2A and C2B. Lee examined how each domain functions in this role. C2B drives the fast fusion of vesicles with the membrane, and requires C2A to dive into the membrane and activate the fusion machinery that promotes mixing of the two lipid membranes.

The second major requirement for neurons is to prevent these fusion events until a calcium signal arrives. Otherwise, neuronal signals flood the brain and wreak havoc, which leads to such neurological disorders as epilepsy. “We found that a protein known as complexin binds to the fusion machinery and prevents it from working until the calcium signal comes,” says MIT affiliate Ramon Jorquera, first author of the Dec. 2 paper, which examines the interplay of complexin and synaptotagmin.

Complexin functions as a fusion clamp, keeping the vesicle from fusing with the synaptic membrane until synaptotagmin senses the influx of calcium and sets the extremely quick fusion process in motion.

This finding is important, Littleton says, because complexin is severely reduced in many neurological and psychological diseases, indicating these disease states may experience too many uncontrolled spontaneous release events. This reduction itself doesn’t cause the diseases, but it may contribute to the phenotypes.

The researchers conducted these studies using the fruit fly, a valuable model organism because of the ease of doing genetic manipulations and neuronal recordings. They created flies in which they deleted or over-expressed various combinations of the genes for the complexin and synaptotagmin proteins, which determined the contribution of each to evoked and spontaneous neurotransmitter release. For example, deleting the complexin clamp caused a 100-fold increase in spontaneous minis; taking away the calcium-sensing synaptotagmin protein eliminated it all.

The researchers also focused on a type of synapse that is representative of the majority of synapses in the human central nervous system — those that release the excitatory neurotransmitter glutamate.

“Because this same machinery appears to play a similar role in mammals, we think we can gain valuable understanding about how it is controlled in humans too,” Littleton says. “Our long-term goal is to learn how neurons normally talk to each other, and how this process goes awry during neurological and psychiatric diseases. This insight might ultimately allow us to restore proper synaptic function and brain communication in disease states.”

Sarah Huntwork-Rodriguez, Yulia Akbergenova and Richard W. Cho, all of the Picower Institute, BCS and the Department of Biology, also contributed to the Dec. 2 paper. Their work was supported by a National Institutes of Health grant and the PEW Latin American Fellows Program in the Biomedical Sciences.

Akbergenova and Zhuo Guan, of the Picower Institute, BCS and the Department of Biology, also contributed to the Jan. 2 paper. This work was supported by an NIH grant.

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Brain waves encode rules for behavior

One of the biggest puzzles in neuroscience is how our brains encode thoughts, such as perceptions and memories, at the cellular level. Some evidence suggests that ensembles of neurons represent each unique piece of information, but no one knows just what these ensembles look like, or how they form.

A new study from researchers at MIT and Boston University (BU) sheds light on how neural ensembles form thoughts and support the flexibility to change one’s mind. The research team, led by Earl Miller, the Picower Professor of Neuroscience at MIT, identified groups of neurons that encode specific behavioral rules by oscillating in synchrony with each other.

The results suggest that the nature of conscious thought may be rhythmic, according to the researchers, who published their findings in the Nov. 21 issue of Neuron.

“As we talk, thoughts float in and out of our heads. Those are all ensembles forming and then reconfiguring to something else. It’s been a mystery how the brain does this,” says Miller, who is also a member of MIT’s Picower Institute for Learning and Memory. “That’s the fundamental problem that we’re talking about — the very nature of thought itself.”

Rules for behavior

The researchers identified two neural ensembles in the brains of monkeys trained to respond to objects based on either their color or orientation. This task requires cognitive flexibility — the ability to switch between two distinct sets of rules for behavior.

“Effectively what they’re doing is focusing on some parts of information in the world and ignoring others. Which behavior they’re doing depends on the context,” says Tim Buschman, an MIT postdoc and one of the lead authors of the paper.

As the animals switched between tasks, the researchers measured the brain waves produced in different locations throughout the prefrontal cortex, where most planning and thought takes place. Those waves are generated by rhythmic fluctuations of neurons’ electrical activity.

When the animals responded to objects based on orientation, the researchers found that certain neurons oscillated at high frequencies that produce so-called beta waves. When color was the required rule, a different ensemble of neurons oscillated in the beta frequency. Some neurons overlapped, belonging to more than one group, but each ensemble had its own distinctive pattern.

Interestingly, the researchers also saw oscillations in the low-frequency alpha range among neurons that make up the orientation rule ensemble, but only when the color rule was being applied. The researchers believe that the alpha waves, which have been associated with suppression of brain activity, help to quiet the neurons that trigger the orientation rule.

“What this suggests is that orientation was dominant, and color was weaker. The brain was throwing this blast of alpha at the orientation ensemble to shut it up, so the animal could use the weaker ensemble,” Miller says.

The findings could explain how the brain can create any appropriate behavioral response to the countless possible combinations of stimuli, rules and required actions, says Pascal Fries, director of the Ernst Strungmann Institute for Neuroscience in Frankfurt, Germany.

“We likely compose the appropriate neuronal assembly on the fly through synchronization,” says Fries, who was not part of the research team. “The number of combinatorial possibilities is enormous, just like the number of possible 10-digit telephone numbers is.”

Eric Denovellis, a graduate student at Boston University, is also a lead author of the paper. Other authors are Cinira Diogo, a former Picower Institute postdoc, and Daniel Bullock, a professor of cognitive and neural systems at BU.

Oscillation as consciousness

The researchers are now trying to figure out how these neural ensembles coordinate their activity as the brain switches back and forth between different rules, or thoughts. Some neuroscientists have theorized that deeper brain structures, such as the thalamus, handle this coordination, but no one knows for sure, Miller says. “It’s one of the biggest mysteries of cognition, what controls your thoughts,” he says.

This work could also help unravel the neural basis of consciousness.

“The most fundamental characteristic of consciousness is its limited capacity. You only can hold a very few thoughts in mind simultaneously,” Miller says. These oscillations may explain why that is: Previous studies have shown that when an animal is holding two thoughts in mind, two different ensembles oscillate in beta frequencies, out of phase with one another.

“That immediately suggests why there’s a limited capacity to consciousness: Only so many balls can be kept in the air at the same time, only a limited amount of information can fit into one oscillatory cycle,” Miller says. Disruptions of these oscillations may be involved in neurological disorders such as schizophrenia; studies have shown that patients with schizophrenia have reduced beta oscillations.

The research was funded by the National Science Foundation and the National Institute of Mental Health.

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Boyden to share prestigious brain prize

Ed Boyden, a faculty member in the MIT Media Lab and the McGovern Institute for Brain Research, was today named a recipient of the 2013 Grete Lundbeck European Brain Research Prize. The 1 million Euro prize is awarded for the development of optogenetics, a technology that makes it possible to control brain activity using light.

The Brain Prize is awarded annually by the Denmark-based Lundbeck Foundation for outstanding contributions to European neuroscience. Boyden is recognized for work done in collaboration with Karl Deisseroth at Stanford University, which builds on earlier discoveries by four European researchers: Ernst Bamberg, Georg Nagel and Peter Hegemann in Germany, and Gero Miesenböck, now in Oxford, U.K. The prize will be shared equally between all six researchers.

The idea of using light to control brain activity was suggested by Francis Crick in 1999, and Miesenbock performed a proof of concept demonstration in 2002, showing that light-sensitive proteins obtained from the eyes of fruit-flies could be used to activate mammalian neurons. A further breakthrough was enabled by the discovery of channelrhodopsin-2 (ChR2), a light-activated ion channel from a common pond algal species that had been characterized by Hegemann in Martinsried and by Nagel and Bamberg in Frankfurt.

The application of ChR2 to neuroscience was pioneered by Boyden and Deisseroth at Stanford University, where Deisseroth is now a faculty member. In a collaboration that began when Boyden was a graduate student and Deisseroth a postdoctoral fellow, they obtained the ChR2 gene from Nagel and Bamberg, expressed it in cultured neurons, and pulsed the dish with blue light to see whether it could trigger neural activity. The first experiment was performed in August 2004, and it worked first time; as Boyden recounted in a recent historical article, “serendipity had struck — the molecule was good enough in its wild-type form to be used in neurons right away.”

They reported this result in 2005, in a landmark paper in Nature Neuroscience that has now been cited more than 600 times. Their method, later dubbed “optogenetics,” is now used by hundreds of labs worldwide and is also being explored for a wide range of potential therapeutic applications. In announcing the Brain Prize, the chairman of the selection committee, Professor Colin Blakemore, described optogenetics as “arguably the most important technical advance in neuroscience in the past 40 years.”

Boyden joined the MIT faculty in 2006, where he is now the Benesse Career Development Professor in the Media Lab, with joint appointments at the McGovern Institute for Brain Research and in the Departments of Biological Engineering and Brain and Cognitive Sciences. His contributions have been recognized by numerous awards and honors, including the inaugural AF Harvey Prize and the 2011 Perl/UNC prize (shared with Karl Deisseroth and with Feng Zhang, also at MIT). He continues to develop novel optogenetic tools, along with many other technologies for understanding and manipulating neural circuits within the living brain.

Boyden's work was supported by the Fannie and John Hertz Foundation, the Helen Hay Whitney Foundation, the McKnight Foundation, Jerry and Marge Burnett, DARPA and the Department of Defense, Google, Harvard/MIT Joint Grants Program in Basic Neuroscience, Human Frontiers Science Program, IET A. F. Harvey Prize, MIT McGovern Institute and MIT Media Lab, NARSAD, New York Stem Cell Foundation-Robertson Investigator Award, NIH, NSF, Paul Allen Distinguished Investigator in Neuroscience Award, Shelly Razin, SkTech, Alfred P. Sloan Foundation, the Society for Neuroscience Research Award for Innovation in Neuroscience (RAIN), and the Wallace H. Coulter Foundation.

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Simons Center for the Social Brain offering seed grants, postdoc fellowships

The Simons Center for the Social Brain (SCSB) at MIT is pleased to announce its 2013 Round 1 funding opportunities for faculty seed grants and postdoctoral fellowships. The deadline for applications is Feb. 28, 2013.

Mission and goals
The mission of the Simons Center for the Social Brain is to understand the neural mechanisms underlying social cognition and behavior, and to translate this knowledge into better diagnosis and treatment of autism spectrum disorders.

Neural correlates of social cognition and behavior exist in diverse species, and the underlying mechanisms will be studied in both humans and relevant model organisms and systems. We expect that experimental approaches will take advantage of strengths at MIT in genetics and genomics, molecular and cell biology, analyses of neural circuits and systems, cognitive psychology, mathematics and engineering.

Seed grants
MIT faculty members with an interest in autism research may apply as the PI on a seed research grant. We seek innovative research projects that are directly relevant to autism and that bridge at least two different MIT labs, or one MIT lab and another at a Boston-area institution (typically a hospital). The expectation is that the seed funds will enable the collection of pilot data on bold new projects, bringing the work to the point where it can be funded through standard channels after the first year. This mechanism will provide a single year of support, at a maximum level of $100,000 in direct costs (indirect costs need not be included in the budget).

The project must involve one MIT faculty member as PI and at least one other independent researcher as co-PI from a different lab. When a MIT PI applies with a co-PI from another Boston-area institution, the funds will be budgeted for spending at MIT. Successful applicants can apply later for a second year of funding, but the application will be considered in competition with all submitted applications (including new ones).?

Postdoctoral Fellowships
Applications for postdoctoral fellowships (named Simons Postdoctoral Fellowships) are sought from candidates with PhD or MD degrees who aim to conduct research at MIT that is relevant to autism. These prestigious fellowships are open to candidates nationwide. They are designed to enhance and showcase autism research at MIT and will be awarded to candidates who propose innovative research bridging at least two different labs.

Each postdoctoral applicant must have a primary advisor who is a MIT faculty member, and a secondary advisor who is an independent researcher at another MIT lab or Boston-area institution. While the fellowships are open to candidates currently at MIT, our goal is to attract outstanding external candidates. MIT faculty members are encouraged to bring these fellowships to the attention of exceptional candidates who wish to come to MIT for postdoctoral training as Simons Fellows.?

The Simons Postdoctoral Fellowships will provide a competitive stipend plus an allowance for health insurance, travel and research-related expenses. The fellowships will be awarded for 2 years, conditional upon satisfactory progress at the end of the first year.?

For information on how to apply for either seed grants or postdoctoral fellowships, please visit the SCSB website.

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3Q: Robert Desimone on the federal BRAIN Initiative

Mapping the human brain, with its billions of neurons, is one of science’s most elusive projects. But a new federal program — the $100 million Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative — could help neuroscientists at MIT and other institutions unlock some of the brain’s mysteries.

How will MIT contribute to the initiative’s goals? How will the initiative impact research already being done at MIT and in the Boston area? How will science benefit? Robert Desimone, the Doris and Don Berkey Professor of Neuroscience and director of MIT’s McGovern Institute for Brain Research — and one of four MIT researchers selected to attend the initiative’s White House announcement on April 2 — discussed these questions with MIT News.

Q. What types of new technologies will be developed to achieve the goals of the initiative? And what are the benefits of the initiative, in terms of better understanding the human brain and treatment of neurological disorders?

A. Among the technologies being discussed are large arrays of nanoscale electrodes; robotic devices for massively parallel whole-cell recordings; new optical methods for imaging activity deep within the brain; and tools from molecular genetics that would allow neurons to store records of their own activity and which we could read out at a later time. We also need better ways to assess biological measures beyond electrical activity — gene expression, for example.

Much of this work will be done in animal models, but we must also develop noninvasive methods so we can relate what we learn from animals to what can be measured in human subjects. And finally, we will also need new analytical methods, including a lot of computing power, if we are to make sense of all these new data and to understand how 100 billion neurons can work together as a system.

When neurons interact with each other in large numbers, new phenomena emerge — much as new social phenomena emerge when large numbers of people interact in groups. Understanding these large-scale interactions will be important if we are to understand the basis of both normal behavior and the altered behaviors seen in many brain disorders. There is evidence that both autism and schizophrenia, for example, involve abnormal synchronous activity across widespread neural populations.

Q. What will MIT’s role be in the initiative? How will MIT collaborate with other Boston-area institutions (and institutions around the nation) to achieve the initiative’s goals?

A. MIT is well-positioned to contribute to the BRAIN Initiative, as many of our researchers are already leaders in developing new technologies for neuroscience. One example is optogenetics, a method for controlling brain activity with light that is already revolutionizing the field.

At the McGovern Institute, we have established a neurotechnology program that provides seed funding for neuroscientists to work with engineers, computer scientists, materials scientists and so on, both within and beyond MIT. We’ve already supported more than 20 such projects, some of which have now turned into major research programs.

We’re very fortunate to have so many top research and clinical institutions in Boston, and we have strong collaborations with many of them. The Martinos Center at the McGovern Institute, where we do human neuroimaging, shares strong ties with its sister center at Massachusetts General Hospital, and also has collaborations with many other local hospitals and universities. Some of us are also members of a Boston-wide initiative to understand the activity of large neural populations, funded by a grant from the National Science Foundation. We also have faculty affiliated with the Broad Institute, and with the Stanley Center for Psychiatric Research, which is tremendously helpful for our work on psychiatric disease. 

Q. How will the initiative affect the research already being done at MIT and other facilities in the Boston area, including MIT’s neighbors in Kendall Square?

A. MIT labs will apply for funding through the BRAIN Initiative as soon as the funding mechanisms are established. Many of us hope that President Obama’s support will encourage private foundations and individuals to contribute.

MIT has a strong track record of working with industry, and we will certainly need to do that if our discoveries are to lead to new therapies. Kendall Square has a great concentration of biotech and high-tech companies, and several large pharmaceutical companies also have a strong presence here. I see them as natural collaborators on the BRAIN Initiative, especially given the huge unmet need for new treatments for brain disease.

Beyond new therapies, I believe the new technologies developed through BRAIN will lead to many other spinoff products, from new optical devices to intelligent machines. The president said it well: Scientific research has had a great return on investment.

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Your child's brain on math: Don't bother?

By Sharon Begley

NEW YORK | Mon Apr 29, 2013 5:02pm EDT

NEW YORK (Reuters) - Parents whose children are struggling with math often view intense tutoring as the best way to help them master crucial skills, but a new study released on Monday suggests that for some kids even that is a lost cause.

According to the research, the size of one key brain structure and the connections between it and other regions can help identify the 8- and 9-year olds who will hardly benefit from one-on-one math instruction.

"We could predict how much a child learned from the tutoring based on measures of brain structure and connectivity," said Vinod Menon, a professor of psychiatry and behavioral sciences at Stanford University School of Medicine, who led the research.

The study, published in the online edition of Proceedings of the National Academy of Sciences, is the first to use brain imaging to look for a connection between brain attributes and the ability to learn arithmetic. But despite its publication in a well-respected journal, the research immediately drew criticism.

Jonathan Moreno, professor of medical ethics at the University of Pennsylvania, fears that some parents and teachers might "give up now" on a math-challenged child. "If it gets into the popular consciousness that it's wise to have your kid's brain checked out" before making decisions about academic options, he said, "that raises huge issues."

Menon and his fellow scientists agree that their research shouldn't lead to hasty conclusions. They are exploring whether any interventions might change the brain in such a way that children who struggle with math can benefit more from tutoring.

Just as learning to juggle increases the amount of gray matter in the area of adult brains that is responsible for spatial attention, said Menon, maybe something could pump up regions relevant to learning arithmetic before a child begins math tutoring.

Until then, he said "it's conceivable" that parents will interpret the new study as saying some kids cannot benefit from math tutoring, "and give up before even trying. How this plays out is far from clear."

MENTAL MATH

The study was conceived as a way to understand why some children benefit more than others from math instruction, said study co-author Lynn Fuchs, professor of special education at Vanderbilt University and an expert on ways to improve reading and math skills in students with learning disabilities.

For the research, the scientists first ran several tests on 24 third-graders to measure their IQ, working memory and reading and math ability. The children also underwent brain imaging. Structural MRI (magnetic resonance imaging) revealed the size and shape of various regions, while functional MRIs revealed connections among them.

Then the children received 22 one-on-one tutoring sessions, spread over eight weeks, for eight to nine hours per week. The tutoring emphasized number knowledge (principles like 5 + 4 = 4 + 5, and that many pairs of numbers add up to, say, 9) and fast-paced mental math ("quick, what is 6 + 9?").

After the tutoring, the children all improved in their arithmetic ability, solving more problems correctly and more quickly. But the amount of improvement varied enormously, from 8 percent to 198 percent.

None of the measures - pre-tutoring IQ score, working memory and math skills - predicted how much a child would improve.

But when the scientists compared each child's improvement with his or her pre-tutoring brain images, two connections jumped out. The volume of gray matter (neurons) in the right hippocampus, one of the twin structures crucial for forming memories, varied by about 10 percent in the children, Stanford's Menon said. The strength of the wiring between the hippocampus and the prefrontal cortex and the basal ganglia varied by about 15 percent. Both predicted how much a child's math skills improved with tutoring, the scientists reported.

The prefrontal cortex, behind the forehead, "is important for cognitive control, which plays a role in the formation of long-term memories," Menon said. The basal ganglia, tucked under the brain's outer surface, "is involved in habit formation and procedural memory," such as how to add numbers.

"Children with a larger right hippocampus and greater connectivity between the hippocampus and these two structures improved their arithmetic problem-solving skills more," said Menon.

These brain features explained 25 percent to 55 percent of the variation in improvement after math tutoring, he said. That, of course, leaves almost half of the difference among children to be explained by other factors.

Among the concerns raised about the study is its size. It enrolled only two dozen children, on a par with many neuroimaging studies but quite small for research that might influence people's behavior, said psychologist Scott Lilienfeld of Emory University.

"This is very, very preliminary evidence that brain measurements might tell you something that psychological measurements don't," said Lilienfeld, co-author with psychiatrist Sally Satel of an upcoming book, "Brainwashed: The Seductive Appeal of Mindless Neuroscience," that critiques some uses of neuroimaging. "It's important to see if the findings hold up in a second sample, and if other labs corroborate this."

Because brain images seem more rigorous than psychological measures, he said, there is a risk that parents and educators will interpret the study as definitive evidence that some children are doomed to be innumerate.

"Caution has to be the watchword here," he said.

(Reporting by Sharon Begley; Editing by Michele Gershberg and Douglas Royalty)

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